The whole is the collection of all the elements that make up it, and the elements are the most basic units that make up the whole.

A sample is a collection of elements extracted from the population in a certain way.

Sampling refers to the process of selecting or extracting a part of elements in a certain way from the set of all elements that make up a certain population.

Sampling unit is the basic unit used for a direct sampling

The sampling frame, also known as the sampling range, refers to the list of all sampling units in the population during a direct sampling

It is a comprehensive description of a certain variable in the population or a comprehensive quantitative expression of a certain characteristic of all elements in the population.

It is a comprehensive description of a certain variable in the sample, or a comprehensive quantitative expression of a certain feature of all elements in the sample.

It is the probability that the overall parameter value falls within a certain interval of the sample statistical value, or in other words, it is the degree of certainty that the overall parameter value falls within a certain interval of the sample statistical value.

Reflects the reliability of sampling

It refers to the error range between the sample statistical value and the overall parameter value under a certain degree of confidence.

Confidence intervals reflect the accuracy of sampling

probability sampling

non-probability sampling

It is the most basic form of probability sampling, which is to directly select n elements from a population containing N elements to form a sample according to the principle of equal probability (N > n)

(1) Drawing lots

(2) Random number table (random number table)

It is a method of sorting the elements of the population by number, then calculating a certain interval, and then extracting elements according to this fixed interval to form a sample.

①Number each individual in the population in order

② Calculate the sampling interval by dividing the population size by the sample size K (sampling interval) = N (population size) / n (sample size)

③ Among the first K individuals, use simple random sampling to extract an individual, and record the number of this individual (assuming that the number of the selected individual is A), which is called the random starting point

④ In the sampling frame, starting from A, one individual is selected from every K individuals. That is, the numbers of the extracted individuals are A, A+K, A 2K, ... A ( n -1)K;

⑤ These n individuals are combined to form a sample of the population.

The prerequisite for systematic sampling is that the arrangement of elements in the population should be random relative to the research variables, and there should be no regular distribution related to the research variables. Otherwise, the results of systematic sampling will produce large errors.

2 situations

It first divides all units in the population into several types or levels according to certain characteristics or signs, and then uses simple random sampling or systematic sampling to extract a subsample from each type or level. Finally, these subsamples are samples that together form the population

① Reduce sampling errors and improve sampling accuracy without increasing sample size

② It is very convenient to understand the situation at different levels within the population, and to conduct separate research or comparison on different levels or categories within the population

Standard issues for layering

layered proportions Proportional sampling and non-proportional sampling (distinguish the applicability of the two)

A method of randomly selecting some small groups from the population, and then forming a survey sample from all the elements of the selected small groups.

①Advantages

②Disadvantages

stratified sampling

cluster sampling

Assume that the population of our survey is a collection of all cities in the country, and we want to draw a sample of 100 cities. What methods can be used to accomplish this? (Simple random sampling, systematic sampling, stratified sampling, cluster sampling...)

According to the affiliation or hierarchical relationship of the sampling elements, the sampling process is divided into several stages. e.g. University - College - Major - Class - Student

①Advantages

②Disadvantages

Note: Keep a balance between categories and individuals

It means that the researcher selects people who meet by chance as the survey objects in a convenient way according to the actual situation, or only selects those who are closest and easiest to find as the survey subjects.

At the entrance of public places; using newspapers and magazines; the teacher conducts surveys using students in the class he teaches as a survey sample

It is a method by which the investigator selects and determines the objects of investigation based on the research objectives and his or her own subjective analysis.

Researchers should try their best to stratify the population based on various factors that may affect the research variables, and find out the proportion of members with various characteristics in the population, using chance sampling or judgment sampling methods to Select the survey objects so that the composition and proportion of the members in the sample in terms of the above factors and various characteristics are as close as possible to the overall situation.

(1) Different purposes

(2) Different methods

is the number of cases included in the sample. According to the views of some social survey experts, the sample size in social surveys cannot be less than 100 cases at least.

(1) Overall scale

(2) Requirements for certainty and accuracy of inference

(3) Overall degree of heterogeneity

(4) Funds, manpower and time available to investigators